Plan de negocio para la fabricación de una crema corporal natural elaborada con manteca de cacao ecuatoriano para su exportación a Ontario-Canadá
Bibliographic record
Abstract
Demand for sustainable organic cosmetic products, also known as bio-cosmetics, is increasing in Canada (Pro Ecuador, 2017). The tendency to consume such products is due to people having become more environmentally conscious and have realized how harmful the use of traditional cosmetic products can be to their skin. As Ecuador recognized worldwide as the best cocoa producer, the idea of creating a company to deal with the production and export of a natural body cream made with Ecuadorian cocoa butter to Canada was born. Responsible processes involving working with organic suppliers, using organic ingredients and packaging that can be recycled will be used for the production of this cream. For this reason, the present work has the main objective of developing a business plan to determine the feasibility of creating a producer and exporter of natural body creams made with Ecuadorian cocoa butter in Ontario, Canada. Macro and micro environment analyses were carried out in order to determine the possible opportunities present for this project. On the other hand, qualitative and quantitative market research was carried out, with the aim of determining the tastes and preferences of potential customers. Through the methodologies mentioned above, positive results were obtained with respect to the acceptance of natural body cream in the Canadian market. Likewise, based on the results obtained, marketing strategies were formulated to position the product offered to the customer. Finally, a financial plan is made with a 5-year projection, with an initial investment of $55,504.36. As a result, a positive net present value of $62,362.71 and an internal return rate of 47.57 percentage is obtained, making the project viable.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".